Features is the description of the image contents which could be corner, blob or edge. Corners are one of the most important feature to describe image, therefore there are many algorithms to detect corners such as Harris, FAST, SUSAN, etc. Harris is a method for corner detection and it is an efficient and accurate feature detection method. Harris corner detection is rotation invariant but it isn’t scale invariant. This paper presents an efficient harris corner detector invariant to scale, this improvement done by using gaussian function with different scales. The experimental results illustrate that it is very useful to use Gaussian linear equation to deal with harris weakness.

Abstract

         Most of the industrial organization in the world became suffering from the problem of the pollution of the poisonous chemicals things, this urged to depend on the principle of the responsible production, because it has the positive role by dealing with these chemical things and to safe the health of the society, due to the main goal of this study is to restrict the role responsible production in accomplishing the system of the environmental management through an actual study in the northern gas company in Kirkuk province, the topic has acquired a big importance bacause there were a limited number of studies and res

This paper is submitted as anew approach to simulate manufacturing control & planning system to define the problem of designing control system on the needs for materials.

Production planning & control is a total and complex operation, resides in the essence of manufacturing companies operations. The successful process of production planning and control systems is critical for the staying of manufacturing organizations in markets leading to the increasing consumer competition and which dominate most of manufacturing sectors because of the market oriented economy , thus , what has happened previously , that the companies possessed a great inventory of crude material, components, and groupings and they use in flexible techni

Gaslift reactors are employed in several bioapplications due to their characteristics of cost-effectiveness and high efficiency. However, the nutrient and thermal gradient is one of the obstacles that stand in the way of its widespread use in biological applications. The diagnosis, analysis, and tracking of fluid paths in external draft tube gaslift bioreactor-type are the main topics of the current study. Several parameters were considered to assess the mixing efficiency such as downcomer-to-rizer diameter ratio (Ded/Dr), the position of the diffuser to the height of bioreactor ratio (Pd/Lr), and gas bubble size (Db). The multiple regression of liquid velocity indicates the optimal setting: Ded/Dr is (0.5), Pd/Lr is (0.02), and Db

A series of new imides compounds[1-4] were synthesized from reaction of tetrachlorophthalic anhydride or nitro phthalic anhydride or malic anhydride or Succinic anhydride with 4-amino benzene thiol under fusion conditions. Chloroacetic acid has been added after compounds [1-4] reacted with distilled H2O and Na2CO3, producing compounds [5-8]. In benzene, compounds [5-8] also interacted with the thionyl chloride to produce [9-12]. Poly (vinyl alcohol) was chemically modified by reacting PVA with compounds [9-12] and dimethyl formamide to produce compounds [13-16]. Iron oxide nanoparticles (IONPs) are mixed with modified PVA [13-16] to create nanocomposites [17-20]. Spectral and analytical data from synthesized compounds, such as 1H-NMR, FTI

Weibull Distribution is one of most important distribution and it is mainly used in reliability and in distribution of life time. The study handled two parameter and three-parameter Weibull Distribution in addition to five –parameter Bi-Weibull distribution. The latter being very new and was not mentioned before in many of the previous references. This distribution depends on both the two parameter and the three –parameter Weibull distributions by using the scale parameter (α) and the shape parameter (b) in the first and adding the location parameter (g)to the second and then joining them together to produce a distribution with five parameters.

The flexible joint robot (FJR) typically experiences parametric variations, nonlinearities, underactuation, noise propagation, and external disturbances which seriously degrade the FJR tracking. This article proposes an adaptive integral sliding mode controller (AISMC) based on a singular perturbation method and two state observers for the FJR to achieve high performance. First, the underactuated FJR is modeled into two simple second-order fast and slow subsystems by using Olfati transformation and singular perturbation method, which handles underactuation while reducing noise amplification. Then, the AISMC is proposed to effectively accomplish the desired tracking performance, in which the integral sliding surface is designed to reduce cha

Traditionally, path selection within routing is formulated as a shortest path optimization problem. The objective function for optimization could be any one variety of parameters such as number of hops, delay, cost...etc. The problem of least cost delay constraint routing is studied in this paper since delay constraint is very common requirement of many multimedia applications and cost minimization captures the need to
distribute the network. So an iterative algorithm is proposed in this paper to solve this problem. It is appeared from the results of applying this algorithm that it gave the optimal path (optimal solution) from among multiple feasible paths (feasible solutions).

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes